Please note that the venue of the conference has changed. DS-2008 will be taking place in Budapest, Hungary .
Discovery Science 2008 Logo
Call for Papers
Paper Submission
Accepted Papers
Important Dates
Program Committee
Registration and Visa
Venue and Travel
Invited Talks


The conference is co-located with ALT 2008 (19th International Conference on Agorithmic Learning Theory). It starts on Monday, October 13th, with two tutorials, scheduled as follows:

  • 13:30-15:30: Tutorial 1
    Saso Dzeroski: Constraint-Based Data Mining and Inductive Queries
  • 15:30-16:00: Coffee Break
  • 16:00-18:00: Tutorial 2
    João Gama: Mining from Data Streams: Issues and Challenges
  • 18:30-20:00: Steering Committee Meeting
  • 18:30 Welcome Reception

The table below presents the schedule for the other three days of the conference. Note that further info about the invited talks can be found on the Invited Talks page.

Time Tuesday, 14 October Wednesday, 15 October Thursday, 16 October
09:00-10:00 Morning Invited Talks
Heikki Mannila
Finding Total and Partial Orders from Data for Seriation
László Lovász
Some Mathematics behind Graph Property Testing
Imre Csiszár
On Iterative Algorithms with an Information Geometry Background
10:00-10:15 Coffee Break
10:15-11:30 Learning 1 Discovery Processes Structured Data
Timo Aho, Tapio Elomaa and Jussi Kujala
Unsupervised Classifier Selection Based on Two-Sample Test

Frederik Janssen and Johannes Furnkranz
An Empirical Investigation of the Trade-Off Between Consistency and Coverage in Rule Learning Heuristics

Albrecht Zimmermann
Ensemble-Trees: Leveraging Ensemble Power inside Decision Trees
Gauvain Bourgne and Vincent Corruble
A Framework for Knowledge Discovery in a Society of Agents

Christopher Dartnell, Eric Martin, and Jean Sallantin
Learning from each other

Wolfgang Kienreich and Peter Kraker
Comparative Evaluation of Two Systems for the Visual Navigation of Encyclopedia Knowledge Spaces
Fedja Hadzic, Henry Tan, and Tharam Dillon
Mining Unordered Distance-constrained Embedded Subtrees

Akihiko Izutani and Kuniaki Uehara
A Modeling Approach using Multiple Graphs for Semi-Supervised Learning

Seiji Murakami, Koichiro Doi, and Akihiro Yamamoto
Finding Frequent Patterns from Compressed Tree-structured Data
11:30-11:40 Short Break
11:40-12:30 Feature Selection Association Rules Text Analysis
Mikko Korpela, Harri Makinen, Mika Sulkava, Pekka Nojd, and Jaakko Hollmen
Smoothed Prediction of the Onset of Tree Stem Radius Increase Based on Temperature Patterns

Gemma C. Garriga, Antti Ukkonen, and Heikki Mannila
Feature Selection in Taxonomies with Applications to Paleontology
Jose L. Balcazar
Deduction Schemes for Association Rules

Laszlo Szathmary, Petko Valtchev, Amedeo Napoli, and Robert Godin
Constructing Iceberg Lattices from Frequent Closures Using Generators
Ata Kaban
A probabilistic neighbourhood translation approach for non-standard text categorisation

Takashi Uenura, Daisuke Ikeda, and Hiroki Arimura
Unsupervised Spam Detection by Document Complexity Estimation
12:30-14:00 Lunch Break
14:00-15:00 Afternoon Invited Talks
Tom Mitchell
Computational Models of Neural Representations in the Human Brain
Daniel A. Keim
Visual Analytics: Combining Automated Discovery with Interactive Visualizations
15:00-15:10 Short Break
15:10-16:50 Learning 2 Clustering
Beau Piccart, Jan Struyf and Hendrik Blockeel
Empirical Asymmetric Selective Transfer in Multi-Objective Decision Trees

Werner Uwents and Hendrik Blockeel
A comparison between neural network methods for learning aggregate functions

Elena Ikonomovska and Joao Gama
Learning Model Trees from Data Streams

Kazuyuki Narisawa, Hideo Bannai, Kohei Hatano, Shunsuke Inenaga and Masayuki Takeda
String Kernels Based on Variable-Length-Don't-Care Patterns
Natthakan Iam-on, Tossapon Boongoon, and Simon Garrett
Refining Pairwise Similarity Matrix for Cluster Ensemble Problem with Cluster Relations

Haytham Elghazel, Tetsuya Yoshida, and Mohand-Said Hacid
An Integrated Graph and Probability Based Clustering Framework for Sequential Data

Alberto Faro, Daniela Giordano, and Francesco Maiorana
Input noise robustness and sensitivity analysis to improve large datasets clustering by using the GRID

Kadim Tasdemir and Erzsebet Merenyi
Cluster analysis in remote sensing spectral imagery through graph representation and advanced SOM visualization
16:50-17:10 Coffee Break
17:10-18:25 Learning and Chemistry "Impromtu talks"
Kurt De Grave, Jan Ramon, and Luc De Raedt
Active Learning for High Throughput Screening

Frederic Pennerath, Geraldine Polaillon, and Amedeo Napoli
Mining Graph Intervals to Extract Characteristic Reaction Patterns

Leander Schietgat, Jan Ramon, Maurice Bruynooghe, and Hendrik Blockeel
An Efficiently Computable Graph-based Metric for the Classification of Small Molecules

Any participant can propose to give a short talk within this session
19:00- Business Meeting Banquet

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